Find latest salaries

# Table: Salary
# 
# +---------------+---------+
# | Column Name   | Type    |
# +---------------+---------+
# | emp_id        | int     |
# | firstname     | varchar |
# | lastname      | varchar |
# | salary        | varchar |
# | department_id | varchar |
# +---------------+---------+
# (emp_id, salary) is the primary key (combination of columns with unique values) for this table.
# Each row contains employees details and their yearly salaries, however, some of the records are old and contain outdated salary information.
# 
# Write a solution to find the current salary of each employee assuming that salaries increase each year. Output their emp_id, firstname, lastname, salary, and department_id.
# 
# Return the result table ordered by emp_id in ascending order.
# 
# The result format is in the following example.
#
# Example 1:
# Input:
# Salary table:
# +--------+-----------+----------+--------+---------------+
# | emp_id | firstname | lastname | salary | department_id |
# +--------+-----------+----------+--------+---------------+
# | 1      | Todd      | Wilson   | 110000 | D1006         |
# | 1      | Todd      | Wilson   | 106119 | D1006         |
# | 2      | Justin    | Simon    | 128922 | D1005         |
# | 2      | Justin    | Simon    | 130000 | D1005         |
# | 3      | Kelly     | Rosario  | 42689  | D1002         |
# | 4      | Patricia  | Powell   | 162825 | D1004         |
# | 4      | Patricia  | Powell   | 170000 | D1004         |
# | 5      | Sherry    | Golden   | 44101  | D1002         |
# | 6      | Natasha   | Swanson  | 79632  | D1005         |
# | 6      | Natasha   | Swanson  | 90000  | D1005         |
# +--------+-----------+----------+--------+---------------+
# Output:
# +--------+-----------+----------+--------+---------------+
# | emp_id | firstname | lastname | salary | department_id |
# +--------+-----------+----------+--------+---------------+
# | 1      | Todd      | Wilson   | 110000 | D1006         |
# | 2      | Justin    | Simon    | 130000 | D1005         |
# | 3      | Kelly     | Rosario  | 42689  | D1002         |
# | 4      | Patricia  | Powell   | 170000 | D1004         |
# | 5      | Sherry    | Golden   | 44101  | D1002         |
# | 6      | Natasha   | Swanson  | 90000  | D1005         |
# +--------+-----------+----------+--------+---------------+
# 
# Explanation:
# - emp_id 1 has two records with a salary of 110000, 106119 out of these 110000 is an updated salary (Assuming salary is increasing each year)
# - emp_id 2 has two records with a salary of 128922, 130000 out of these 130000 is an updated salary.
# - emp_id 3 has only one salary record so that is already an updated salary.
# - emp_id 4 has two records with a salary of 162825, 170000 out of these 170000 is an updated salary.
# - emp_id 5 has only one salary record so that is already an updated salary.
# - emp_id 6 has two records with a salary of 79632, 90000 out of these 90000 is an updated salary.

import pandas as pd

def find_latest_salaries(salary: pd.DataFrame) -> pd.DataFrame:
  idx = salary.groupby('emp_id')['salary'].idxmax()
  return salary.loc[idx].sort_values('emp_id')